Chapter 1- Introduction to MLOPS
Chapter 2- Linux Basics Foundation
Chapter 3- Git and Github Foundation
Introduction to clustering
Hierarchical clustering
Chapter 4- Data version control
Chapter 5- Docker Foundation (Devops)
Introduction to Assoiciation rule
Apriori Algorithm
Eclat Algorithm
Chapter 6- Kubernetes foundation (Devops)
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Introduction to Reinforcement learning
Basics of Markov Decision Processes
Exploration vs Exploitation Trade-off
Chapter 7- Prometheus and Grafana (MLOPS)
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Hyperparameter tunning
Imbalanced classification
✔✔✔
Chapter 8- Jenkins (Devops)
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Hyperparameter tunning
Imbalanced classification
Chapter 9- MLFLOW
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Hyperparameter tunning
Imbalanced classification
Chapter 10- Tensorflow Extended
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Hyperparameter tunning
Imbalanced classification
Chapter 11- Kubeflow
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Hyperparameter tunning
Imbalanced classification
Chapter 12- Gitlab Foundations
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